Pandas Profiling Report

Dataset statistics

Number of variables	33
Number of observations	4009
Missing cells	58098
Missing cells (%)	43.9%
Duplicate rows	3
Duplicate rows (%)	0.1%
Total size in memory	1.0 MiB
Average record size in memory	264.0 B

Variable types

Unsupported	4
Categorical	15
Numeric	4
DateTime	1
Text	9

Alerts

`opinion-of-the-field-of-study` has constant value "useful"	Constant
`other-position` has constant value "pkojihgufyudtyrstuiyguoipj"	Constant
Dataset has 3 (0.1%) duplicate rows	Duplicates
`Program-of-Study` is highly overall correlated with `status`	High correlation
`amount-of-salary-and-allownce` is highly overall correlated with `departement` and 5 other fields	High correlation
`departement` is highly overall correlated with `amount-of-salary-and-allownce` and 2 other fields	High correlation
`department` is highly overall correlated with `improvement-suggestions` and 1 other fields	High correlation
`education-level` is highly overall correlated with `status`	High correlation
`employment-status` is highly overall correlated with `departement` and 5 other fields	High correlation
`gender` is highly overall correlated with `amount-of-salary-and-allownce`	High correlation
`graduation-year` is highly overall correlated with `product-or-service-offered` and 1 other fields	High correlation
`improvement-suggestions` is highly overall correlated with `amount-of-salary-and-allownce` and 6 other fields	High correlation
`industry-sector` is highly overall correlated with `amount-of-salary-and-allownce` and 4 other fields	High correlation
`nik` is highly overall correlated with `position` and 2 other fields	High correlation
`position` is highly overall correlated with `amount-of-salary-and-allownce` and 5 other fields	High correlation
`product-or-service-offered` is highly overall correlated with `graduation-year` and 2 other fields	High correlation
`quality-of-education` is highly overall correlated with `employment-status` and 3 other fields	High correlation
`status` is highly overall correlated with `Program-of-Study` and 10 other fields	High correlation
`unit-of-profit` is highly overall correlated with `graduation-year` and 2 other fields	High correlation
`employment-status` is highly imbalanced (99.4%)	Imbalance
`employment-status` has 2000 (49.9%) missing values	Missing
`first-job` has 2000 (49.9%) missing values	Missing
`year` has 1000 (24.9%) missing values	Missing
`company-name` has 2000 (49.9%) missing values	Missing
`industry-sector` has 2000 (49.9%) missing values	Missing
`Address` has 2000 (49.9%) missing values	Missing
`last-name` has 2002 (49.9%) missing values	Missing
`department` has 2002 (49.9%) missing values	Missing
`position` has 2000 (49.9%) missing values	Missing
`opinion-of-the-field-of-study` has 4002 (99.8%) missing values	Missing
`month` has 1000 (24.9%) missing values	Missing
`salary-meet-the-minimum-wage` has 2000 (49.9%) missing values	Missing
`first-name` has 2002 (49.9%) missing values	Missing
`amount-of-salary-and-allownce` has 2000 (49.9%) missing values	Missing
`other-position` has 4008 (> 99.9%) missing values	Missing
`last_name` has 2007 (50.1%) missing values	Missing
`email` has 2007 (50.1%) missing values	Missing
`first_name` has 2007 (50.1%) missing values	Missing
`departement` has 2007 (50.1%) missing values	Missing
`education-level` has 3009 (75.1%) missing values	Missing
`institution` has 3009 (75.1%) missing values	Missing
`Program-of-Study` has 3009 (75.1%) missing values	Missing
`product-or-service-offered` has 3009 (75.1%) missing values	Missing
`amount-of-profit` has 3009 (75.1%) missing values	Missing
`unit-of-profit` has 3009 (75.1%) missing values	Missing
`nik` is highly skewed (γ1 = 25.28997864)	Skewed
`_id` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`first-job` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`salary-meet-the-minimum-wage` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`amount-of-profit` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`graduation-year` has 62 (1.5%) zeros	Zeros

Reproduction

Analysis started	2024-07-12 08:57:19.355482
Analysis finished	2024-07-12 08:57:35.275546
Duration	15.92 seconds
Software version	ydata-profiling v4.8.3
Download configuration	config.json

_id
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

employment-status
Categorical

HIGH CORRELATION IMBALANCE MISSING

Distinct	2
Distinct (%)	0.1%
Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

daily-freelance	2008
permanent	1

Length

Max length	15
Median length	15
Mean length	14.997013
Min length	9

Characters and Unicode

Total characters	30129
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	daily-freelance
2nd row	daily-freelance
3rd row	permanent
4th row	daily-freelance
5th row	daily-freelance

Common Values

Value	Count	Frequency (%)
daily-freelance	2008	50.1%
permanent	1	< 0.1%
(Missing)	2000	49.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
daily-freelance	2008	> 99.9%
permanent	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
e	6026	20.0%
a	4017	13.3%
l	4016	13.3%
n	2010	6.7%
r	2009	6.7%
d	2008	6.7%
i	2008	6.7%
y	2008	6.7%
-	2008	6.7%
f	2008	6.7%
Other values (4)	2011	6.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	30129	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	6026	20.0%
a	4017	13.3%
l	4016	13.3%
n	2010	6.7%
r	2009	6.7%
d	2008	6.7%
i	2008	6.7%
y	2008	6.7%
-	2008	6.7%
f	2008	6.7%
Other values (4)	2011	6.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	30129	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	6026	20.0%
a	4017	13.3%
l	4016	13.3%
n	2010	6.7%
r	2009	6.7%
d	2008	6.7%
i	2008	6.7%
y	2008	6.7%
-	2008	6.7%
f	2008	6.7%
Other values (4)	2011	6.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	30129	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	6026	20.0%
a	4017	13.3%
l	4016	13.3%
n	2010	6.7%
r	2009	6.7%
d	2008	6.7%
i	2008	6.7%
y	2008	6.7%
-	2008	6.7%
f	2008	6.7%
Other values (4)	2011	6.7%

first-job
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

year
Real number (ℝ)

MISSING

Distinct	59
Distinct (%)	2.0%
Missing	1000
Missing (%)	24.9%
Infinite	0
Infinite (%)	0.0%
Mean	2000.4646

Minimum	1909
Maximum	2024
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	31.4 KiB

Quantile statistics

Minimum	1909
5-th percentile	1986
Q1	1995
median	2002
Q3	2008
95-th percentile	2012
Maximum	2024
Range	115
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.4675131
Coefficient of variation (CV)	0.0047326571
Kurtosis	7.848282
Mean	2000.4646
Median Absolute Deviation (MAD)	6
Skewness	-1.7202442
Sum	6019398
Variance	89.633803
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2006	159	4.0%
2011	156	3.9%
2004	155	3.9%
2009	155	3.9%
2008	147	3.7%
2007	147	3.7%
2012	134	3.3%
1992	128	3.2%
2010	128	3.2%
2003	127	3.2%
Other values (49)	1573	39.2%
(Missing)	1000	24.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1909	2	< 0.1%
1953	1	< 0.1%
1955	1	< 0.1%
1958	1	< 0.1%
1959	2	< 0.1%
1960	2	< 0.1%
1962	1	< 0.1%
1963	3	0.1%
1964	6	0.1%
1965	9	0.2%

Value	Count	Frequency (%)
2024	7	0.2%
2013	28	0.7%
2012	134	3.3%
2011	156	3.9%
2010	128	3.2%
2009	155	3.9%
2008	147	3.7%
2007	147	3.7%
2006	159	4.0%
2005	123	3.1%

birthdate
Date

Distinct	495
Distinct (%)	12.3%
Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

Minimum	2001-01-15 00:00:00
Maximum	2024-07-11 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

graduation-year
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	62
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1974.9414

Minimum	0
Maximum	2024
Zeros	62
Zeros (%)	1.5%
Negative	0
Negative (%)	0.0%
Memory size	31.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1987
Q1	2000
median	2008
Q3	2012
95-th percentile	2018
Maximum	2024
Range	2024
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	247.7301
Coefficient of variation (CV)	0.12543669
Kurtosis	59.575265
Mean	1974.9414
Median Absolute Deviation (MAD)	6
Skewness	-7.839233
Sum	7917540
Variance	61370.204
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2011	251	6.3%
2012	243	6.1%
2010	203	5.1%
2014	187	4.7%
2006	187	4.7%
2009	180	4.5%
2008	167	4.2%
2004	156	3.9%
2013	155	3.9%
2015	154	3.8%
Other values (52)	2126	53.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	62	1.5%
1948	1	< 0.1%
1957	1	< 0.1%
1958	1	< 0.1%
1959	1	< 0.1%
1960	1	< 0.1%
1961	1	< 0.1%
1963	2	< 0.1%
1964	6	0.1%
1965	2	< 0.1%

Value	Count	Frequency (%)
2024	1	< 0.1%
2021	12	0.3%
2020	93	2.3%
2019	91	2.3%
2018	84	2.1%
2017	96	2.4%
2016	119	3.0%
2015	154	3.8%
2014	187	4.7%
2013	155	3.9%

company-name
Text

MISSING

Distinct	831
Distinct (%)	41.4%
Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

Length

Max length	99
Median length	55
Mean length	23.365356
Min length	2

Characters and Unicode

Total characters	46941
Distinct characters	72
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	527 ?
Unique (%)	26.2%

Sample

1st row	JIVALOKA
2nd row	JIVALOKA
3rd row	PT Ijoroyo
4th row	JIVALOKA
5th row	JIVALOKA

Value	Count	Frequency (%)
inc	909	14.1%
llc	239	3.7%
pharmaceuticals	237	3.7%
laboratories	182	2.8%
company	133	2.1%
health	103	1.6%
co	89	1.4%
corporation	83	1.3%
ltd	81	1.3%
	81	1.3%
Other values (1047)	4331	67.0%

Most occurring characters

Value	Count	Frequency (%)
	4459	9.5%
a	3769	8.0%
e	2809	6.0%
r	2613	5.6%
n	2504	5.3%
o	2293	4.9%
c	2285	4.9%
i	2204	4.7%
t	1996	4.3%
l	1617	3.4%
Other values (62)	20392	43.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	46941	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	4459	9.5%
a	3769	8.0%
e	2809	6.0%
r	2613	5.6%
n	2504	5.3%
o	2293	4.9%
c	2285	4.9%
i	2204	4.7%
t	1996	4.3%
l	1617	3.4%
Other values (62)	20392	43.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	46941	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	4459	9.5%
a	3769	8.0%
e	2809	6.0%
r	2613	5.6%
n	2504	5.3%
o	2293	4.9%
c	2285	4.9%
i	2204	4.7%
t	1996	4.3%
l	1617	3.4%
Other values (62)	20392	43.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	46941	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	4459	9.5%
a	3769	8.0%
e	2809	6.0%
r	2613	5.6%
n	2504	5.3%
o	2293	4.9%
c	2285	4.9%
i	2204	4.7%
t	1996	4.3%
l	1617	3.4%
Other values (62)	20392	43.4%

industry-sector
Categorical

HIGH CORRELATION MISSING

Distinct	15
Distinct (%)	0.7%
Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

n/a	437
Finance	343
Health Care	236
Consumer Services	233
Technology	194
Other values (10)	566

Length

Max length	21
Median length	16
Mean length	10.10005
Min length	3

Characters and Unicode

Total characters	20291
Distinct characters	37
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	marketing
2nd row	marketing
3rd row	other
4th row	marketing
5th row	marketing

Common Values

Value	Count	Frequency (%)
n/a	437	10.9%
Finance	343	8.6%
Health Care	236	5.9%
Consumer Services	233	5.8%
Technology	194	4.8%
Capital Goods	111	2.8%
Public Utilities	89	2.2%
Energy	81	2.0%
Consumer Non-Durables	73	1.8%
Basic Industries	69	1.7%
Other values (5)	143	3.6%
(Missing)	2000	49.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
n/a	437	15.2%
consumer	362	12.6%
finance	343	11.9%
health	236	8.2%
care	236	8.2%
services	233	8.1%
technology	194	6.7%
capital	111	3.9%
goods	111	3.9%
utilities	89	3.1%
Other values (10)	524	18.2%

Most occurring characters

Value	Count	Frequency (%)
e	2290	11.3%
n	2029	10.0%
a	1799	8.9%
i	1267	6.2%
s	1250	6.2%
r	1199	5.9%
o	1167	5.8%
c	967	4.8%
l	926	4.6%
	867	4.3%
Other values (27)	6530	32.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	20291	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	2290	11.3%
n	2029	10.0%
a	1799	8.9%
i	1267	6.2%
s	1250	6.2%
r	1199	5.9%
o	1167	5.8%
c	967	4.8%
l	926	4.6%
	867	4.3%
Other values (27)	6530	32.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	20291	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	2290	11.3%
n	2029	10.0%
a	1799	8.9%
i	1267	6.2%
s	1250	6.2%
r	1199	5.9%
o	1167	5.8%
c	967	4.8%
l	926	4.6%
	867	4.3%
Other values (27)	6530	32.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	20291	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	2290	11.3%
n	2029	10.0%
a	1799	8.9%
i	1267	6.2%
s	1250	6.2%
r	1199	5.9%
o	1167	5.8%
c	967	4.8%
l	926	4.6%
	867	4.3%
Other values (27)	6530	32.2%

Address
Text

MISSING

Distinct	1271
Distinct (%)	63.3%
Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

Length

Max length	26
Median length	12
Mean length	9.0886013
Min length	5

Characters and Unicode

Total characters	18259
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1096 ?
Unique (%)	54.6%

Sample

1st row	Jl . Bumi Karadenan Permai
2nd row	Jl . Bumi Karadenan Permai
3rd row	Cibinong
4th row	Jl . Bumi Karadenan Permai
5th row	Jl . Bumi Karadenan Permai

Value	Count	Frequency (%)
apt	417	9.4%
suite	416	9.4%
box	411	9.2%
po	411	9.2%
room	396	8.9%
floor	362	8.1%
1st	23	0.5%
15th	23	0.5%
10th	22	0.5%
4th	22	0.5%
Other values (1169)	1943	43.7%

Most occurring characters

Value	Count	Frequency (%)
	2437	13.3%
o	1928	10.6%
1	1194	6.5%
t	1167	6.4%
4	616	3.4%
5	596	3.3%
2	585	3.2%
8	577	3.2%
9	571	3.1%
7	553	3.0%
Other values (29)	8035	44.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	18259	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	2437	13.3%
o	1928	10.6%
1	1194	6.5%
t	1167	6.4%
4	616	3.4%
5	596	3.3%
2	585	3.2%
8	577	3.2%
9	571	3.1%
7	553	3.0%
Other values (29)	8035	44.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	18259	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	2437	13.3%
o	1928	10.6%
1	1194	6.5%
t	1167	6.4%
4	616	3.4%
5	596	3.3%
2	585	3.2%
8	577	3.2%
9	571	3.1%
7	553	3.0%
Other values (29)	8035	44.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	18259	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	2437	13.3%
o	1928	10.6%
1	1194	6.5%
t	1167	6.4%
4	616	3.4%
5	596	3.3%
2	585	3.2%
8	577	3.2%
9	571	3.1%
7	553	3.0%
Other values (29)	8035	44.0%

quality-of-education
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

poor	1165
good	1163
exellent	680
excellent	501
not-satisfied	500

Length

Max length	13
Median length	4
Mean length	6.425792
Min length	4

Characters and Unicode

Total characters	25761
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	good
2nd row	good
3rd row	excellent
4th row	good
5th row	good

Common Values

Value	Count	Frequency (%)
poor	1165	29.1%
good	1163	29.0%
exellent	680	17.0%
excellent	501	12.5%
not-satisfied	500	12.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
poor	1165	29.1%
good	1163	29.0%
exellent	680	17.0%
excellent	501	12.5%
not-satisfied	500	12.5%

Most occurring characters

Value	Count	Frequency (%)
o	5156	20.0%
e	4043	15.7%
l	2362	9.2%
t	2181	8.5%
n	1681	6.5%
d	1663	6.5%
x	1181	4.6%
p	1165	4.5%
r	1165	4.5%
g	1163	4.5%
Other values (6)	4001	15.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	25761	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	5156	20.0%
e	4043	15.7%
l	2362	9.2%
t	2181	8.5%
n	1681	6.5%
d	1663	6.5%
x	1181	4.6%
p	1165	4.5%
r	1165	4.5%
g	1163	4.5%
Other values (6)	4001	15.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	25761	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	5156	20.0%
e	4043	15.7%
l	2362	9.2%
t	2181	8.5%
n	1681	6.5%
d	1663	6.5%
x	1181	4.6%
p	1165	4.5%
r	1165	4.5%
g	1163	4.5%
Other values (6)	4001	15.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	25761	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	5156	20.0%
e	4043	15.7%
l	2362	9.2%
t	2181	8.5%
n	1681	6.5%
d	1663	6.5%
x	1181	4.6%
p	1165	4.5%
r	1165	4.5%
g	1163	4.5%
Other values (6)	4001	15.5%

last-name
Text

MISSING

Distinct	1967
Distinct (%)	98.0%
Missing	2002
Missing (%)	49.9%
Memory size	31.4 KiB

Length

Max length	25
Median length	14
Mean length	7.019432
Min length	3

Characters and Unicode

Total characters	14088
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1931 ?
Unique (%)	96.2%

Sample

1st row	Septanugroho
2nd row	Septanugroho
3rd row	Ismail
4th row	Septanugroho
5th row	Septanugroho

Value	Count	Frequency (%)
de	8	0.4%
septanugroho	6	0.3%
le	5	0.2%
o	4	0.2%
van	4	0.2%
la	3	0.1%
marlow	2	0.1%
pring	2	0.1%
bythway	2	0.1%
pedrol	2	0.1%
Other values (1970)	2002	98.1%

Most occurring characters

Value	Count	Frequency (%)
e	1529	10.9%
a	1109	7.9%
r	1052	7.5%
n	951	6.8%
l	928	6.6%
o	875	6.2%
i	862	6.1%
t	652	4.6%
s	568	4.0%
d	397	2.8%
Other values (46)	5165	36.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	14088	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1529	10.9%
a	1109	7.9%
r	1052	7.5%
n	951	6.8%
l	928	6.6%
o	875	6.2%
i	862	6.1%
t	652	4.6%
s	568	4.0%
d	397	2.8%
Other values (46)	5165	36.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	14088	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1529	10.9%
a	1109	7.9%
r	1052	7.5%
n	951	6.8%
l	928	6.6%
o	875	6.2%
i	862	6.1%
t	652	4.6%
s	568	4.0%
d	397	2.8%
Other values (46)	5165	36.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	14088	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1529	10.9%
a	1109	7.9%
r	1052	7.5%
n	951	6.8%
l	928	6.6%
o	875	6.2%
i	862	6.1%
t	652	4.6%
s	568	4.0%
d	397	2.8%
Other values (46)	5165	36.7%

department
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	0.7%
Missing	2002
Missing (%)	49.9%
Memory size	31.4 KiB

Accounting	186
Sales	184
Business Development	183
Training	182
Legal	173
Other values (9)	1099

Length

Max length	24
Median length	18
Mean length	11.501744
Min length	5

Characters and Unicode

Total characters	23084
Distinct characters	32
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	teknik-otomasi-industri
2nd row	teknik-otomasi-industri
3rd row	rekayasa-perangkat-lunak
4th row	teknik-otomasi-industri
5th row	teknik-otomasi-industri

Common Values

Value	Count	Frequency (%)
Accounting	186	4.6%
Sales	184	4.6%
Business Development	183	4.6%
Training	182	4.5%
Legal	173	4.3%
Engineering	164	4.1%
Marketing	163	4.1%
Services	163	4.1%
Product Management	157	3.9%
Human Resources	156	3.9%
Other values (4)	296	7.4%
(Missing)	2002	49.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
development	324	11.6%
accounting	186	6.7%
sales	184	6.6%
business	183	6.6%
training	182	6.5%
legal	173	6.2%
engineering	164	5.9%
marketing	163	5.9%
services	163	5.9%
management	157	5.6%
Other values (8)	906	32.5%

Most occurring characters

Value	Count	Frequency (%)
e	3245	14.1%
n	2523	10.9%
a	1466	6.4%
i	1411	6.1%
s	1362	5.9%
r	1282	5.6%
g	1190	5.2%
t	1154	5.0%
u	993	4.3%
c	989	4.3%
Other values (22)	7469	32.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	23084	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	3245	14.1%
n	2523	10.9%
a	1466	6.4%
i	1411	6.1%
s	1362	5.9%
r	1282	5.6%
g	1190	5.2%
t	1154	5.0%
u	993	4.3%
c	989	4.3%
Other values (22)	7469	32.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	23084	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	3245	14.1%
n	2523	10.9%
a	1466	6.4%
i	1411	6.1%
s	1362	5.9%
r	1282	5.6%
g	1190	5.2%
t	1154	5.0%
u	993	4.3%
c	989	4.3%
Other values (22)	7469	32.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	23084	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	3245	14.1%
n	2523	10.9%
a	1466	6.4%
i	1411	6.1%
s	1362	5.9%
r	1282	5.6%
g	1190	5.2%
t	1154	5.0%
u	993	4.3%
c	989	4.3%
Other values (22)	7469	32.4%

status
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

working	2009
studying	1000
entrepreneur	1000

Length

Max length	12
Median length	7
Mean length	8.4966326
Min length	7

Characters and Unicode

Total characters	34063
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	working
2nd row	working
3rd row	working
4th row	working
5th row	working

Common Values

Value	Count	Frequency (%)
working	2009	50.1%
studying	1000	24.9%
entrepreneur	1000	24.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
working	2009	50.1%
studying	1000	24.9%
entrepreneur	1000	24.9%

Most occurring characters

Value	Count	Frequency (%)
r	5009	14.7%
n	5009	14.7%
e	4000	11.7%
i	3009	8.8%
g	3009	8.8%
w	2009	5.9%
o	2009	5.9%
k	2009	5.9%
t	2000	5.9%
u	2000	5.9%
Other values (4)	4000	11.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	34063	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	5009	14.7%
n	5009	14.7%
e	4000	11.7%
i	3009	8.8%
g	3009	8.8%
w	2009	5.9%
o	2009	5.9%
k	2009	5.9%
t	2000	5.9%
u	2000	5.9%
Other values (4)	4000	11.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	34063	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	5009	14.7%
n	5009	14.7%
e	4000	11.7%
i	3009	8.8%
g	3009	8.8%
w	2009	5.9%
o	2009	5.9%
k	2009	5.9%
t	2000	5.9%
u	2000	5.9%
Other values (4)	4000	11.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	34063	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	5009	14.7%
n	5009	14.7%
e	4000	11.7%
i	3009	8.8%
g	3009	8.8%
w	2009	5.9%
o	2009	5.9%
k	2009	5.9%
t	2000	5.9%
u	2000	5.9%
Other values (4)	4000	11.7%

position
Categorical

HIGH CORRELATION MISSING

Distinct	14
Distinct (%)	0.7%
Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

Marketing	181
Training	181
Legal	177
Research and Development	175
Sales	171
Other values (9)	1124

Length

Max length	24
Median length	15
Mean length	11.587855
Min length	5

Characters and Unicode

Total characters	23280
Distinct characters	30
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	accounting
2nd row	accounting
3rd row	other
4th row	accounting
5th row	accounting

Common Values

Value	Count	Frequency (%)
Marketing	181	4.5%
Training	181	4.5%
Legal	177	4.4%
Research and Development	175	4.4%
Sales	171	4.3%
Human Resources	170	4.2%
Services	169	4.2%
Business Development	166	4.1%
Accounting	162	4.0%
Engineering	161	4.0%
Other values (4)	296	7.4%
(Missing)	2000	49.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
development	341	12.0%
marketing	181	6.4%
training	181	6.4%
legal	177	6.2%
research	175	6.2%
and	175	6.2%
sales	171	6.0%
resources	170	6.0%
human	170	6.0%
services	169	6.0%
Other values (7)	927	32.7%

Most occurring characters

Value	Count	Frequency (%)
e	3353	14.4%
n	2498	10.7%
a	1520	6.5%
i	1368	5.9%
s	1353	5.8%
r	1327	5.7%
g	1171	5.0%
t	1122	4.8%
c	992	4.3%
o	969	4.2%
Other values (20)	7607	32.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	23280	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	3353	14.4%
n	2498	10.7%
a	1520	6.5%
i	1368	5.9%
s	1353	5.8%
r	1327	5.7%
g	1171	5.0%
t	1122	4.8%
c	992	4.3%
o	969	4.2%
Other values (20)	7607	32.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	23280	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	3353	14.4%
n	2498	10.7%
a	1520	6.5%
i	1368	5.9%
s	1353	5.8%
r	1327	5.7%
g	1171	5.0%
t	1122	4.8%
c	992	4.3%
o	969	4.2%
Other values (20)	7607	32.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	23280	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	3353	14.4%
n	2498	10.7%
a	1520	6.5%
i	1368	5.9%
s	1353	5.8%
r	1327	5.7%
g	1171	5.0%
t	1122	4.8%
c	992	4.3%
o	969	4.2%
Other values (20)	7607	32.7%

opinion-of-the-field-of-study
Categorical

CONSTANT MISSING

Distinct	1
Distinct (%)	14.3%
Missing	4002
Missing (%)	99.8%
Memory size	31.4 KiB

useful	7

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	42
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	useful
2nd row	useful
3rd row	useful
4th row	useful
5th row	useful

Common Values

Value	Count	Frequency (%)
useful	7	0.2%
(Missing)	4002	99.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
useful	7	100.0%

Most occurring characters

Value	Count	Frequency (%)
u	14	33.3%
s	7	16.7%
e	7	16.7%
f	7	16.7%
l	7	16.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	42	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
u	14	33.3%
s	7	16.7%
e	7	16.7%
f	7	16.7%
l	7	16.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	42	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
u	14	33.3%
s	7	16.7%
e	7	16.7%
f	7	16.7%
l	7	16.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	42	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
u	14	33.3%
s	7	16.7%
e	7	16.7%
f	7	16.7%
l	7	16.7%

gender
Categorical

HIGH CORRELATION

Distinct	9
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

Male	1801
Female	1792
Polygender	77
Agender	73
Genderqueer	73
Other values (4)	193

Length

Max length	11
Median length	10
Mean length	5.4554752
Min length	4

Characters and Unicode

Total characters	21871
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	male
2nd row	male
3rd row	male
4th row	male
5th row	male

Common Values

Value	Count	Frequency (%)
Male	1801	44.9%
Female	1792	44.7%
Polygender	77	1.9%
Agender	73	1.8%
Genderqueer	73	1.8%
Non-binary	69	1.7%
Genderfluid	59	1.5%
Bigender	58	1.4%
male	7	0.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
male	1808	45.1%
female	1792	44.7%
polygender	77	1.9%
agender	73	1.8%
genderqueer	73	1.8%
non-binary	69	1.7%
genderfluid	59	1.5%
bigender	58	1.4%

Most occurring characters

Value	Count	Frequency (%)
e	6218	28.4%
l	3736	17.1%
a	3669	16.8%
M	1801	8.2%
m	1799	8.2%
F	1792	8.2%
r	482	2.2%
n	478	2.2%
d	399	1.8%
g	208	1.0%
Other values (13)	1289	5.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	21871	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	6218	28.4%
l	3736	17.1%
a	3669	16.8%
M	1801	8.2%
m	1799	8.2%
F	1792	8.2%
r	482	2.2%
n	478	2.2%
d	399	1.8%
g	208	1.0%
Other values (13)	1289	5.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	21871	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	6218	28.4%
l	3736	17.1%
a	3669	16.8%
M	1801	8.2%
m	1799	8.2%
F	1792	8.2%
r	482	2.2%
n	478	2.2%
d	399	1.8%
g	208	1.0%
Other values (13)	1289	5.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	21871	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	6218	28.4%
l	3736	17.1%
a	3669	16.8%
M	1801	8.2%
m	1799	8.2%
F	1792	8.2%
r	482	2.2%
n	478	2.2%
d	399	1.8%
g	208	1.0%
Other values (13)	1289	5.9%

month
Categorical

MISSING

Distinct	12
Distinct (%)	0.4%
Missing	1000
Missing (%)	24.9%
Memory size	31.4 KiB

september	261
may	261
january	260
april	258
july	256
Other values (7)	1713

Length

Max length	9
Median length	7
Mean length	6.148222
Min length	3

Characters and Unicode

Total characters	18500
Distinct characters	21
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	october
2nd row	october
3rd row	april
4th row	october
5th row	october

Common Values

Value	Count	Frequency (%)
september	261	6.5%
may	261	6.5%
january	260	6.5%
april	258	6.4%
july	256	6.4%
august	254	6.3%
december	252	6.3%
march	249	6.2%
october	243	6.1%
june	243	6.1%
Other values (2)	472	11.8%
(Missing)	1000	24.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
september	261	8.7%
may	261	8.7%
january	260	8.6%
april	258	8.6%
july	256	8.5%
august	254	8.4%
december	252	8.4%
march	249	8.3%
october	243	8.1%
june	243	8.1%
Other values (2)	472	15.7%

Most occurring characters

Value	Count	Frequency (%)
e	2737	14.8%
r	2227	12.0%
a	1774	9.6%
u	1499	8.1%
m	1263	6.8%
b	1228	6.6%
y	1009	5.5%
j	759	4.1%
t	758	4.1%
c	744	4.0%
Other values (11)	4502	24.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	18500	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	2737	14.8%
r	2227	12.0%
a	1774	9.6%
u	1499	8.1%
m	1263	6.8%
b	1228	6.6%
y	1009	5.5%
j	759	4.1%
t	758	4.1%
c	744	4.0%
Other values (11)	4502	24.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	18500	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	2737	14.8%
r	2227	12.0%
a	1774	9.6%
u	1499	8.1%
m	1263	6.8%
b	1228	6.6%
y	1009	5.5%
j	759	4.1%
t	758	4.1%
c	744	4.0%
Other values (11)	4502	24.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	18500	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	2737	14.8%
r	2227	12.0%
a	1774	9.6%
u	1499	8.1%
m	1263	6.8%
b	1228	6.6%
y	1009	5.5%
j	759	4.1%
t	758	4.1%
c	744	4.0%
Other values (11)	4502	24.3%

salary-meet-the-minimum-wage
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	2000
Missing (%)	49.9%
Memory size	31.4 KiB

improvement-suggestions
Categorical

HIGH CORRELATION

Distinct	10
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	31.4 KiB

hard to get a job for a while	681
it's hard for getting job after school life	666
great i'm joinning top university	655
saya berhasil masuk ptn impian	500
saya berhasil masuk ptn walaupun bukan impian saya	500
Other values (5)	1007

Length

Max length	52
Median length	36
Mean length	38.448241
Min length	14

Characters and Unicode

Total characters	154139
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	aegbahwg9yhagw
2nd row	aegbahwg9yhagw
3rd row	oiufyutycuvbjoigouiyctu
4th row	improve the cleaning services
5th row	aegbahwg9yhagw

Common Values

Value	Count	Frequency (%)
hard to get a job for a while	681	17.0%
it's hard for getting job after school life	666	16.6%
great i'm joinning top university	655	16.3%
saya berhasil masuk ptn impian	500	12.5%
saya berhasil masuk ptn walaupun bukan impian saya	500	12.5%
saya sangat sulit untuk masuk kuliah	500	12.5%
saya bisa masuk kuliah walaupun harus bersusah payah	500	12.5%
aegbahwg9yhagw	4	0.1%
improve the cleaning services	2	< 0.1%
oiufyutycuvbjoigouiyctu	1	< 0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
saya	2500	9.1%
masuk	2000	7.3%
a	1362	4.9%
for	1347	4.9%
hard	1347	4.9%
job	1347	4.9%
berhasil	1000	3.6%
kuliah	1000	3.6%
walaupun	1000	3.6%
ptn	1000	3.6%
Other values (28)	13661	49.6%

Most occurring characters

Value	Count	Frequency (%)
	23555	15.3%
a	20044	13.0%
i	10963	7.1%
s	10491	6.8%
u	8660	5.6%
t	8495	5.5%
n	7790	5.1%
r	6674	4.3%
h	6204	4.0%
e	6184	4.0%
Other values (16)	45079	29.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	154139	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	23555	15.3%
a	20044	13.0%
i	10963	7.1%
s	10491	6.8%
u	8660	5.6%
t	8495	5.5%
n	7790	5.1%
r	6674	4.3%
h	6204	4.0%
e	6184	4.0%
Other values (16)	45079	29.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	154139	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	23555	15.3%
a	20044	13.0%
i	10963	7.1%
s	10491	6.8%
u	8660	5.6%
t	8495	5.5%
n	7790	5.1%
r	6674	4.3%
h	6204	4.0%
e	6184	4.0%
Other values (16)	45079	29.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	154139	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	23555	15.3%
a	20044	13.0%
i	10963	7.1%
s	10491	6.8%
u	8660	5.6%
t	8495	5.5%
n	7790	5.1%
r	6674	4.3%
h	6204	4.0%
e	6184	4.0%
Other values (16)	45079	29.2%

first-name
Text

MISSING

Distinct	1775
Distinct (%)	88.4%
Missing	2002
Missing (%)	49.9%
Memory size	31.4 KiB

Length

Max length	13
Median length	11
Mean length	5.9646238
Min length	2

Characters and Unicode

Total characters	11971
Distinct characters	53
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1571 ?
Unique (%)	78.3%

Sample

1st row	Muhammad Aris
2nd row	Muhammad Aris
3rd row	Fadli
4th row	Muhammad Aris
5th row	Muhammad Aris

Value	Count	Frequency (%)
muhammad	6	0.3%
aris	6	0.3%
ann-marie	4	0.2%
ricky	3	0.1%
moe	3	0.1%
andrus	3	0.1%
woodman	3	0.1%
evyn	3	0.1%
kalie	3	0.1%
hubie	3	0.1%
Other values (1766)	1976	98.2%

Most occurring characters

Value	Count	Frequency (%)
e	1382	11.5%
a	1262	10.5%
i	1027	8.6%
n	918	7.7%
r	878	7.3%
l	829	6.9%
o	605	5.1%
t	468	3.9%
y	356	3.0%
d	353	2.9%
Other values (43)	3893	32.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11971	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1382	11.5%
a	1262	10.5%
i	1027	8.6%
n	918	7.7%
r	878	7.3%
l	829	6.9%
o	605	5.1%
t	468	3.9%
y	356	3.0%
d	353	2.9%
Other values (43)	3893	32.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11971	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1382	11.5%
a	1262	10.5%
i	1027	8.6%
n	918	7.7%
r	878	7.3%
l	829	6.9%
o	605	5.1%
t	468	3.9%
y	356	3.0%
d	353	2.9%
Other values (43)	3893	32.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11971	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1382	11.5%
a	1262	10.5%
i	1027	8.6%
n	918	7.7%
r	878	7.3%
l	829	6.9%
o	605	5.1%
t	468	3.9%
y	356	3.0%
d	353	2.9%
Other values (43)	3893	32.5%

nik
Real number (ℝ)

HIGH CORRELATION SKEWED

Distinct	4003
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.0509333 × 10¹²

Minimum	2789728
Maximum	3.2010104 × 10¹⁵
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	31.4 KiB

Quantile statistics

Minimum	2789728
5-th percentile	5.615157 × 10⁸
Q1	2.5683375 × 10⁹
median	4.9640021 × 10⁹
Q3	7.536463 × 10⁹
95-th percentile	9.484503 × 10⁹
Maximum	3.2010104 × 10¹⁵
Range	3.2010104 × 10¹⁵
Interquartile range (IQR)	4.9681255 × 10⁹

Descriptive statistics

Standard deviation	1.2479845 × 10¹⁴
Coefficient of variation (CV)	24.707998
Kurtosis	642.92936
Mean	5.0509333 × 10¹²
Median Absolute Deviation (MAD)	2.4884714 × 10⁹
Skewness	25.289979
Sum	2.0249192 × 10¹⁶
Variance	1.5574653 × 10²⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3.20101044 × 10¹⁵	6	0.1%
364263113	2	< 0.1%
7359596084	1	< 0.1%
9613605398	1	< 0.1%
3913654992	1	< 0.1%
1349899720	1	< 0.1%
3413832425	1	< 0.1%
9026399286	1	< 0.1%
2302489101	1	< 0.1%
5504508622	1	< 0.1%
Other values (3993)	3993	99.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2789728	1	< 0.1%
11768266	1	< 0.1%
11973110	1	< 0.1%
12698601	1	< 0.1%
15481883	1	< 0.1%
27305635	1	< 0.1%
30557143	1	< 0.1%
38172054	1	< 0.1%
49084534	1	< 0.1%
49558374	1	< 0.1%

Value	Count	Frequency (%)
3.20101044 × 10¹⁵	6	0.1%
1.023073197 × 10¹⁵	1	< 0.1%
9999197620	1	< 0.1%
9998176859	1	< 0.1%
9997159225	1	< 0.1%
9996511863	1	< 0.1%
9994461982	1	< 0.1%
9990387109	1	< 0.1%
9981592773	1	< 0.1%
9980664274	1	< 0.1%

amount-of-salary-and-allownce
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	1987
Distinct (%)	98.9%
Missing	2000
Missing (%)	49.9%
Infinite	0
Infinite (%)	0.0%
Mean	414191.87

Minimum	148
Maximum	1.2083402 × 10⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	31.4 KiB

Quantile statistics

Minimum	148
5-th percentile	5808.6
Q1	26813
median	51891
Q3	76090
95-th percentile	95303.8
Maximum	1.2083402 × 10⁸
Range	1.2083387 × 10⁸
Interquartile range (IQR)	49277

Descriptive statistics

Standard deviation	6593351.9
Coefficient of variation (CV)	15.918593
Kurtosis	330.46217
Mean	414191.87
Median Absolute Deviation (MAD)	24747
Skewness	18.221969
Sum	8.3211146 × 10⁸
Variance	4.3472289 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120834021	6	0.1%
99351	2	< 0.1%
56643	2	< 0.1%
81963	2	< 0.1%
80460	2	< 0.1%
21418	2	< 0.1%
38828	2	< 0.1%
78148	2	< 0.1%
99761	2	< 0.1%
36133	2	< 0.1%
Other values (1977)	1985	49.5%
(Missing)	2000	49.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
148	1	< 0.1%
171	1	< 0.1%
176	1	< 0.1%
248	1	< 0.1%
309	1	< 0.1%
417	1	< 0.1%
498	1	< 0.1%
566	1	< 0.1%
582	1	< 0.1%
614	1	< 0.1%

Value	Count	Frequency (%)
120834021	6	0.1%
5000000	1	< 0.1%
99961	1	< 0.1%
99960	1	< 0.1%
99893	1	< 0.1%
99815	1	< 0.1%
99785	1	< 0.1%
99761	2	< 0.1%
99731	1	< 0.1%
99689	1	< 0.1%

other-position
Text

CONSTANT MISSING

Distinct	1
Distinct (%)	100.0%
Missing	4008
Missing (%)	> 99.9%
Memory size	31.4 KiB

Length

Max length	26
Median length	26
Mean length	26
Min length	26

Characters and Unicode

Total characters	26
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	pkojihgufyudtyrstuiyguoipj

Value	Count	Frequency (%)
pkojihgufyudtyrstuiyguoipj	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
u	4	15.4%
i	3	11.5%
y	3	11.5%
p	2	7.7%
o	2	7.7%
j	2	7.7%
g	2	7.7%
t	2	7.7%
k	1	3.8%
h	1	3.8%
Other values (4)	4	15.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	26	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
u	4	15.4%
i	3	11.5%
y	3	11.5%
p	2	7.7%
o	2	7.7%
j	2	7.7%
g	2	7.7%
t	2	7.7%
k	1	3.8%
h	1	3.8%
Other values (4)	4	15.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	26	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
u	4	15.4%
i	3	11.5%
y	3	11.5%
p	2	7.7%
o	2	7.7%
j	2	7.7%
g	2	7.7%
t	2	7.7%
k	1	3.8%
h	1	3.8%
Other values (4)	4	15.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	26	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
u	4	15.4%
i	3	11.5%
y	3	11.5%
p	2	7.7%
o	2	7.7%
j	2	7.7%
g	2	7.7%
t	2	7.7%
k	1	3.8%
h	1	3.8%
Other values (4)	4	15.4%

last_name
Text

MISSING

Distinct	1966
Distinct (%)	98.2%
Missing	2007
Missing (%)	50.1%
Memory size	31.4 KiB

Length

Max length	15
Median length	13
Mean length	6.9905095
Min length	3

Characters and Unicode

Total characters	13995
Distinct characters	55
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1930 ?
Unique (%)	96.4%

Sample

1st row	Josefer
2nd row	Josefer
3rd row	Olorenshaw
4th row	Averall
5th row	Ragg

Value	Count	Frequency (%)
de	11	0.5%
mc	6	0.3%
le	4	0.2%
laxon	2	0.1%
drynan	2	0.1%
perfili	2	0.1%
lyptrit	2	0.1%
janosevic	2	0.1%
millwater	2	0.1%
sapsed	2	0.1%
Other values (1965)	1997	98.3%

Most occurring characters

Value	Count	Frequency (%)
e	1514	10.8%
a	1032	7.4%
r	987	7.1%
n	946	6.8%
l	915	6.5%
o	913	6.5%
i	890	6.4%
t	678	4.8%
s	591	4.2%
d	408	2.9%
Other values (45)	5121	36.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13995	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1514	10.8%
a	1032	7.4%
r	987	7.1%
n	946	6.8%
l	915	6.5%
o	913	6.5%
i	890	6.4%
t	678	4.8%
s	591	4.2%
d	408	2.9%
Other values (45)	5121	36.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13995	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1514	10.8%
a	1032	7.4%
r	987	7.1%
n	946	6.8%
l	915	6.5%
o	913	6.5%
i	890	6.4%
t	678	4.8%
s	591	4.2%
d	408	2.9%
Other values (45)	5121	36.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13995	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1514	10.8%
a	1032	7.4%
r	987	7.1%
n	946	6.8%
l	915	6.5%
o	913	6.5%
i	890	6.4%
t	678	4.8%
s	591	4.2%
d	408	2.9%
Other values (45)	5121	36.6%

email
Text

MISSING

Distinct	2001
Distinct (%)	> 99.9%
Missing	2007
Missing (%)	50.1%
Memory size	31.4 KiB

Length

Max length	36
Median length	31
Mean length	21.938062
Min length	13

Characters and Unicode

Total characters	43920
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2000 ?
Unique (%)	99.9%

Sample

1st row	pjosefer0@typepad.com
2nd row	pjosefer0@typepad.com
3rd row	lolorenshaw0@yolasite.com
4th row	laverall1@umn.edu
5th row	eragg2@bizjournals.com

Value	Count	Frequency (%)
pjosefer0@typepad.com	2	0.1%
tjedraszczykd@ebay.co.uk	1	< 0.1%
lolorenshaw0@yolasite.com	1	< 0.1%
laverall1@umn.edu	1	< 0.1%
eragg2@bizjournals.com	1	< 0.1%
fmenloe3@wiley.com	1	< 0.1%
rknappen4@admin.ch	1	< 0.1%
ecluff5@abc.net.au	1	< 0.1%
rblaszkiewicz6@blogspot.com	1	< 0.1%
rpeat7@cisco.com	1	< 0.1%
Other values (1991)	1991	99.5%

Most occurring characters

Value	Count	Frequency (%)
o	3782	8.6%
e	3413	7.8%
c	2784	6.3%
a	2623	6.0%
m	2350	5.4%
n	2202	5.0%
.	2192	5.0%
r	2190	5.0%
i	2167	4.9%
@	2002	4.6%
Other values (29)	18215	41.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	43920	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	3782	8.6%
e	3413	7.8%
c	2784	6.3%
a	2623	6.0%
m	2350	5.4%
n	2202	5.0%
.	2192	5.0%
r	2190	5.0%
i	2167	4.9%
@	2002	4.6%
Other values (29)	18215	41.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	43920	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	3782	8.6%
e	3413	7.8%
c	2784	6.3%
a	2623	6.0%
m	2350	5.4%
n	2202	5.0%
.	2192	5.0%
r	2190	5.0%
i	2167	4.9%
@	2002	4.6%
Other values (29)	18215	41.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	43920	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	3782	8.6%
e	3413	7.8%
c	2784	6.3%
a	2623	6.0%
m	2350	5.4%
n	2202	5.0%
.	2192	5.0%
r	2190	5.0%
i	2167	4.9%
@	2002	4.6%
Other values (29)	18215	41.5%

first_name
Text

MISSING

Distinct	1762
Distinct (%)	88.0%
Missing	2007
Missing (%)	50.1%
Memory size	31.4 KiB

Length

Max length	14
Median length	12
Mean length	5.9895105
Min length	2

Characters and Unicode

Total characters	11991
Distinct characters	54
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1551 ?
Unique (%)	77.5%

Sample

1st row	Pietrek
2nd row	Pietrek
3rd row	Leslie
4th row	Lissy
5th row	Emmaline

Value	Count	Frequency (%)
timmy	5	0.2%
manolo	4	0.2%
kyle	4	0.2%
siobhan	3	0.1%
dalli	3	0.1%
nickie	3	0.1%
cornie	3	0.1%
roda	3	0.1%
mal	3	0.1%
hector	3	0.1%
Other values (1752)	1969	98.3%

Most occurring characters

Value	Count	Frequency (%)
e	1481	12.4%
a	1267	10.6%
i	1051	8.8%
n	973	8.1%
r	870	7.3%
l	844	7.0%
o	589	4.9%
t	448	3.7%
s	326	2.7%
y	322	2.7%
Other values (44)	3820	31.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11991	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1481	12.4%
a	1267	10.6%
i	1051	8.8%
n	973	8.1%
r	870	7.3%
l	844	7.0%
o	589	4.9%
t	448	3.7%
s	326	2.7%
y	322	2.7%
Other values (44)	3820	31.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11991	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1481	12.4%
a	1267	10.6%
i	1051	8.8%
n	973	8.1%
r	870	7.3%
l	844	7.0%
o	589	4.9%
t	448	3.7%
s	326	2.7%
y	322	2.7%
Other values (44)	3820	31.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11991	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1481	12.4%
a	1267	10.6%
i	1051	8.8%
n	973	8.1%
r	870	7.3%
l	844	7.0%
o	589	4.9%
t	448	3.7%
s	326	2.7%
y	322	2.7%
Other values (44)	3820	31.9%

departement
Categorical

HIGH CORRELATION MISSING

Distinct	9
Distinct (%)	0.4%
Missing	2007
Missing (%)	50.1%
Memory size	31.4 KiB

teknik-kendaraan-ringan	250
teknik-pemesinan	248
rekayasa-perangkat-lunak	234
bisnis-kontruksi-dan-properti	223
teknik-otomasi-industri	222
Other values (4)	825

Length

Max length	38
Median length	29
Mean length	27.679321
Min length	16

Characters and Unicode

Total characters	55414
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	bisnis-kontruksi-dan-properti
2nd row	bisnis-kontruksi-dan-properti
3rd row	teknik-otomasi-industri
4th row	teknik-kendaraan-ringan
5th row	bisnis-kontruksi-dan-properti

Common Values

Value	Count	Frequency (%)
teknik-kendaraan-ringan	250	6.2%
teknik-pemesinan	248	6.2%
rekayasa-perangkat-lunak	234	5.8%
bisnis-kontruksi-dan-properti	223	5.6%
teknik-otomasi-industri	222	5.5%
desain-pemodelan-informasi-bangunan	217	5.4%
teknik-fabrikasi-logam-dan-manufaktur	212	5.3%
sistem-informasi-jaringan-dan-aplikasi	198	4.9%
teknik-komputer-dan-jaringan	198	4.9%
(Missing)	2007	50.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
teknik-kendaraan-ringan	250	12.5%
teknik-pemesinan	248	12.4%
rekayasa-perangkat-lunak	234	11.7%
bisnis-kontruksi-dan-properti	223	11.1%
teknik-otomasi-industri	222	11.1%
desain-pemodelan-informasi-bangunan	217	10.8%
teknik-fabrikasi-logam-dan-manufaktur	212	10.6%
sistem-informasi-jaringan-dan-aplikasi	198	9.9%
teknik-komputer-dan-jaringan	198	9.9%

Most occurring characters

Value	Count	Frequency (%)
a	7236	13.1%
n	7097	12.8%
i	5647	10.2%
-	5214	9.4%
k	4478	8.1%
e	3614	6.5%
r	3292	5.9%
s	3033	5.5%
t	2862	5.2%
o	1932	3.5%
Other values (10)	11009	19.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	55414	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	7236	13.1%
n	7097	12.8%
i	5647	10.2%
-	5214	9.4%
k	4478	8.1%
e	3614	6.5%
r	3292	5.9%
s	3033	5.5%
t	2862	5.2%
o	1932	3.5%
Other values (10)	11009	19.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	55414	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	7236	13.1%
n	7097	12.8%
i	5647	10.2%
-	5214	9.4%
k	4478	8.1%
e	3614	6.5%
r	3292	5.9%
s	3033	5.5%
t	2862	5.2%
o	1932	3.5%
Other values (10)	11009	19.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	55414	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	7236	13.1%
n	7097	12.8%
i	5647	10.2%
-	5214	9.4%
k	4478	8.1%
e	3614	6.5%
r	3292	5.9%
s	3033	5.5%
t	2862	5.2%
o	1932	3.5%
Other values (10)	11009	19.9%

education-level
Categorical

HIGH CORRELATION MISSING

Distinct	6
Distinct (%)	0.6%
Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

diploma3	184
diploma1/2	180
diploma4	165
other	163
master	156

Length

Max length	10
Median length	8
Mean length	7.559
Min length	5

Characters and Unicode

Total characters	7559
Distinct characters	19
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	diploma1/2
2nd row	other
3rd row	diploma4
4th row	diploma1/2
5th row	diploma1/2

Common Values

Value	Count	Frequency (%)
diploma3	184	4.6%
diploma1/2	180	4.5%
diploma4	165	4.1%
other	163	4.1%
master	156	3.9%
bachelor	152	3.8%
(Missing)	3009	75.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
diploma3	184	18.4%
diploma1/2	180	18.0%
diploma4	165	16.5%
other	163	16.3%
master	156	15.6%
bachelor	152	15.2%

Most occurring characters

Value	Count	Frequency (%)
o	844	11.2%
a	837	11.1%
m	685	9.1%
l	681	9.0%
d	529	7.0%
p	529	7.0%
i	529	7.0%
r	471	6.2%
e	471	6.2%
t	319	4.2%
Other values (9)	1664	22.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7559	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	844	11.2%
a	837	11.1%
m	685	9.1%
l	681	9.0%
d	529	7.0%
p	529	7.0%
i	529	7.0%
r	471	6.2%
e	471	6.2%
t	319	4.2%
Other values (9)	1664	22.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7559	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	844	11.2%
a	837	11.1%
m	685	9.1%
l	681	9.0%
d	529	7.0%
p	529	7.0%
i	529	7.0%
r	471	6.2%
e	471	6.2%
t	319	4.2%
Other values (9)	1664	22.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7559	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	844	11.2%
a	837	11.1%
m	685	9.1%
l	681	9.0%
d	529	7.0%
p	529	7.0%
i	529	7.0%
r	471	6.2%
e	471	6.2%
t	319	4.2%
Other values (9)	1664	22.0%

institution
Text

MISSING

Distinct	947
Distinct (%)	94.7%
Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

Length

Max length	94
Median length	65
Mean length	31.188
Min length	11

Characters and Unicode

Total characters	31188
Distinct characters	87
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	896 ?
Unique (%)	89.6%

Sample

1st row	Oglala Lakota College
2nd row	University of Engineering and Technology Lahore
3rd row	Pukyong National University
4th row	International Colleges of Islamic Science
5th row	Hokkaido Institute of Technology

Value	Count	Frequency (%)
university	538	13.5%
of	285	7.2%
college	134	3.4%
de	120	3.0%
universidad	82	2.1%
state	76	1.9%
institute	59	1.5%
technology	55	1.4%
and	47	1.2%
national	36	0.9%
Other values (1430)	2552	64.1%

Most occurring characters

Value	Count	Frequency (%)
	3003	9.6%
i	2888	9.3%
e	2804	9.0%
n	2168	7.0%
a	2095	6.7%
t	1815	5.8%
r	1676	5.4%
o	1622	5.2%
s	1575	5.1%
l	1170	3.8%
Other values (77)	10372	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	31188	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	3003	9.6%
i	2888	9.3%
e	2804	9.0%
n	2168	7.0%
a	2095	6.7%
t	1815	5.8%
r	1676	5.4%
o	1622	5.2%
s	1575	5.1%
l	1170	3.8%
Other values (77)	10372	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	31188	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	3003	9.6%
i	2888	9.3%
e	2804	9.0%
n	2168	7.0%
a	2095	6.7%
t	1815	5.8%
r	1676	5.4%
o	1622	5.2%
s	1575	5.1%
l	1170	3.8%
Other values (77)	10372	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	31188	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	3003	9.6%
i	2888	9.3%
e	2804	9.0%
n	2168	7.0%
a	2095	6.7%
t	1815	5.8%
r	1676	5.4%
o	1622	5.2%
s	1575	5.1%
l	1170	3.8%
Other values (77)	10372	33.3%

Program-of-Study
Categorical

HIGH CORRELATION MISSING

Distinct	12
Distinct (%)	1.2%
Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

Human Resources	94
Legal	93
Product Management	92
Marketing	90
Services	85
Other values (7)	546

Length

Max length	24
Median length	15
Mean length	11.45
Min length	5

Characters and Unicode

Total characters	11450
Distinct characters	30
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Legal
2nd row	Engineering
3rd row	Product Management
4th row	Product Management
5th row	Services

Common Values

Value	Count	Frequency (%)
Human Resources	94	2.3%
Legal	93	2.3%
Product Management	92	2.3%
Marketing	90	2.2%
Services	85	2.1%
Training	85	2.1%
Support	83	2.1%
Engineering	82	2.0%
Accounting	80	2.0%
Business Development	78	1.9%
Other values (2)	138	3.4%
(Missing)	3009	75.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
development	142	10.2%
human	94	6.8%
resources	94	6.8%
legal	93	6.7%
product	92	6.6%
management	92	6.6%
marketing	90	6.5%
services	85	6.1%
training	85	6.1%
support	83	6.0%
Other values (6)	442	31.8%

Most occurring characters

Value	Count	Frequency (%)
e	1595	13.9%
n	1228	10.7%
a	748	6.5%
r	675	5.9%
i	667	5.8%
s	645	5.6%
g	604	5.3%
t	579	5.1%
u	521	4.6%
c	495	4.3%
Other values (20)	3693	32.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	11450	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1595	13.9%
n	1228	10.7%
a	748	6.5%
r	675	5.9%
i	667	5.8%
s	645	5.6%
g	604	5.3%
t	579	5.1%
u	521	4.6%
c	495	4.3%
Other values (20)	3693	32.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	11450	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1595	13.9%
n	1228	10.7%
a	748	6.5%
r	675	5.9%
i	667	5.8%
s	645	5.6%
g	604	5.3%
t	579	5.1%
u	521	4.6%
c	495	4.3%
Other values (20)	3693	32.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	11450	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1595	13.9%
n	1228	10.7%
a	748	6.5%
r	675	5.9%
i	667	5.8%
s	645	5.6%
g	604	5.3%
t	579	5.1%
u	521	4.6%
c	495	4.3%
Other values (20)	3693	32.3%

product-or-service-offered
Categorical

HIGH CORRELATION MISSING

Distinct	22
Distinct (%)	2.2%
Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

Movies	60
Baby	57
Electronics	56
Jewelry	52
Sports	52
Other values (17)	723

Length

Max length	11
Median length	9
Mean length	6.436
Min length	4

Characters and Unicode

Total characters	6436
Distinct characters	34
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Outdoors
2nd row	Sports
3rd row	Movies
4th row	Toys
5th row	Movies

Common Values

Value	Count	Frequency (%)
Movies	60	1.5%
Baby	57	1.4%
Electronics	56	1.4%
Jewelry	52	1.3%
Sports	52	1.3%
Books	51	1.3%
Games	49	1.2%
Automotive	48	1.2%
Clothing	48	1.2%
Garden	47	1.2%
Other values (12)	480	12.0%
(Missing)	3009	75.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
movies	60	6.0%
baby	57	5.7%
electronics	56	5.6%
jewelry	52	5.2%
sports	52	5.2%
books	51	5.1%
games	49	4.9%
automotive	48	4.8%
clothing	48	4.8%
garden	47	4.7%
Other values (12)	480	48.0%

Most occurring characters

Value	Count	Frequency (%)
o	756	11.7%
e	605	9.4%
s	583	9.1%
t	443	6.9%
r	411	6.4%
i	340	5.3%
l	282	4.4%
a	277	4.3%
u	235	3.7%
y	232	3.6%
Other values (24)	2272	35.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6436	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	756	11.7%
e	605	9.4%
s	583	9.1%
t	443	6.9%
r	411	6.4%
i	340	5.3%
l	282	4.4%
a	277	4.3%
u	235	3.7%
y	232	3.6%
Other values (24)	2272	35.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6436	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	756	11.7%
e	605	9.4%
s	583	9.1%
t	443	6.9%
r	411	6.4%
i	340	5.3%
l	282	4.4%
a	277	4.3%
u	235	3.7%
y	232	3.6%
Other values (24)	2272	35.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6436	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	756	11.7%
e	605	9.4%
s	583	9.1%
t	443	6.9%
r	411	6.4%
i	340	5.3%
l	282	4.4%
a	277	4.3%
u	235	3.7%
y	232	3.6%
Other values (24)	2272	35.3%

amount-of-profit
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

unit-of-profit
Categorical

HIGH CORRELATION MISSING

Distinct	3
Distinct (%)	0.3%
Missing	3009
Missing (%)	75.1%
Memory size	31.4 KiB

week	350
month	331
day	319

Length

Max length	5
Median length	4
Mean length	4.012
Min length	3

Characters and Unicode

Total characters	4012
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	week
2nd row	week
3rd row	month
4th row	day
5th row	month

Common Values

Value	Count	Frequency (%)
week	350	8.7%
month	331	8.3%
day	319	8.0%
(Missing)	3009	75.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
week	350	35.0%
month	331	33.1%
day	319	31.9%

Most occurring characters

Value	Count	Frequency (%)
e	700	17.4%
w	350	8.7%
k	350	8.7%
m	331	8.3%
o	331	8.3%
n	331	8.3%
t	331	8.3%
h	331	8.3%
d	319	8.0%
a	319	8.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4012	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	700	17.4%
w	350	8.7%
k	350	8.7%
m	331	8.3%
o	331	8.3%
n	331	8.3%
t	331	8.3%
h	331	8.3%
d	319	8.0%
a	319	8.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4012	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	700	17.4%
w	350	8.7%
k	350	8.7%
m	331	8.3%
o	331	8.3%
n	331	8.3%
t	331	8.3%
h	331	8.3%
d	319	8.0%
a	319	8.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4012	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	700	17.4%
w	350	8.7%
k	350	8.7%
m	331	8.3%
o	331	8.3%
n	331	8.3%
t	331	8.3%
h	331	8.3%
d	319	8.0%
a	319	8.0%

Auto

Heatmap
Table

	Program-of-Study	amount-of-salary-and-allownce	departement	department	education-level	employment-status	gender	graduation-year	improvement-suggestions	industry-sector	month	nik	position	product-or-service-offered	quality-of-education	status	unit-of-profit	year
Program-of-Study	1.000	NaN	0.000	0.000	0.000	0.000	0.000	0.040	0.000	0.000	0.000	0.016	0.000	0.000	0.000	1.000	0.000	NaN
amount-of-salary-and-allownce	NaN	1.000	1.000	0.091	0.000	0.000	0.924	-0.001	0.999	0.997	0.171	0.001	0.997	0.000	0.068	1.000	0.000	-0.023
departement	0.000	1.000	1.000	0.000	0.000	1.000	0.000	0.025	0.000	0.000	0.033	-0.031	0.000	0.000	0.000	1.000	0.000	0.010
department	0.000	0.091	0.000	1.000	0.042	0.091	0.353	0.014	0.575	0.091	0.057	-0.012	0.091	0.041	0.054	0.705	0.000	-0.006
education-level	0.000	0.000	0.000	0.042	1.000	0.000	0.012	0.036	0.000	0.000	0.000	-0.016	0.000	0.000	0.000	1.000	0.000	NaN
employment-status	0.000	0.000	1.000	0.091	0.000	1.000	0.372	0.039	0.999	0.997	0.000	0.038	0.997	0.000	1.000	1.000	0.000	0.039
gender	0.000	0.924	0.000	0.353	0.012	0.372	1.000	-0.001	0.353	0.351	0.029	-0.002	0.352	0.066	0.000	0.035	0.000	0.015
graduation-year	0.040	-0.001	0.025	0.014	0.036	0.039	-0.001	1.000	0.124	0.000	0.028	0.023	0.031	1.000	0.073	0.123	1.000	-0.008
improvement-suggestions	0.000	0.999	0.000	0.575	0.000	0.999	0.353	0.124	1.000	0.629	0.334	-0.004	0.630	0.000	0.802	0.706	0.000	0.012
industry-sector	0.000	0.997	0.000	0.091	0.000	0.997	0.351	0.000	0.629	1.000	0.039	0.001	0.392	0.000	0.577	1.000	0.000	0.001
month	0.000	0.171	0.033	0.057	0.000	0.000	0.029	0.028	0.334	0.039	1.000	-0.008	0.057	0.025	0.390	0.000	0.039	0.022
nik	0.016	0.001	-0.031	-0.012	-0.016	0.038	-0.002	0.023	-0.004	0.001	-0.008	1.000	0.997	1.000	0.041	0.019	1.000	0.006
position	0.000	0.997	0.000	0.091	0.000	0.997	0.352	0.031	0.630	0.392	0.057	0.997	1.000	0.000	0.579	1.000	0.000	0.038
product-or-service-offered	0.000	0.000	0.000	0.041	0.000	0.000	0.066	1.000	0.000	0.000	0.025	1.000	0.000	1.000	0.000	1.000	0.000	-0.021
quality-of-education	0.000	0.068	0.000	0.054	0.000	1.000	0.000	0.073	0.802	0.577	0.390	0.041	0.579	0.000	1.000	0.463	0.000	-0.023
status	1.000	1.000	1.000	0.705	1.000	1.000	0.035	0.123	0.706	1.000	0.000	0.019	1.000	1.000	0.463	1.000	1.000	-0.012
unit-of-profit	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.039	1.000	0.000	0.000	0.000	1.000	1.000	0.005
year	NaN	-0.023	0.010	-0.006	NaN	0.039	0.015	-0.008	0.012	0.001	0.022	0.006	0.038	-0.021	-0.023	-0.012	0.005	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	_id	employment-status	first-job	year	birthdate	graduation-year	company-name	industry-sector	Address	quality-of-education	last-name	department	status	position	opinion-of-the-field-of-study	gender	month	salary-meet-the-minimum-wage	improvement-suggestions	first-name	nik	amount-of-salary-and-allownce	other-position	last_name	email	first_name	departement	education-level	institution	Program-of-Study	product-or-service-offered	amount-of-profit	unit-of-profit
0	{'$oid': '66903c606e398b6e105dcff8'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	aegbahwg9yhagw	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	{'$oid': '66903d9c6e398b6e105dcff9'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	aegbahwg9yhagw	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	{'$oid': '6690406e6e398b6e105dcffa'}	permanent	yes	2024.0	2006-06-04	2024	PT Ijoroyo	other	Cibinong	excellent	Ismail	rekayasa-perangkat-lunak	working	other	useful	male	april	yes	oiufyutycuvbjoigouiyctu	Fadli	1023073197098097	5000000.0	pkojihgufyudtyrstuiyguoipj	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	{'$oid': '66909195b72fc3ddba24dd30'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	improve the cleaning services	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	{'$oid': '66909195b72fc3ddba24dd31'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	aegbahwg9yhagw	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5	{'$oid': '669099f7b72fc3ddba24dd32'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	improve the cleaning services	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
6	{'$oid': '669099f7b72fc3ddba24dd33'}	daily-freelance	yes	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	yes	aegbahwg9yhagw	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
7	{'$oid': '66909acfb72fc3ddba24dd34'}	daily-freelance	False	1992.0	2024-03-18	1998	Cardinal Health	Finance	Suite 100	poor	NaN	NaN	working	Business Development	NaN	Non-binary	july	False	hard to get a job for a while	NaN	364263113	99351.0	NaN	Josefer	pjosefer0@typepad.com	Pietrek	bisnis-kontruksi-dan-properti	NaN	NaN	NaN	NaN	NaN	NaN
8	{'$oid': '66909addb72fc3ddba24dd35'}	daily-freelance	False	1992.0	2024-03-18	1998	Cardinal Health	Finance	Suite 100	poor	NaN	NaN	working	Business Development	NaN	Non-binary	july	False	hard to get a job for a while	NaN	364263113	99351.0	NaN	Josefer	pjosefer0@typepad.com	Pietrek	bisnis-kontruksi-dan-properti	NaN	NaN	NaN	NaN	NaN	NaN
9	{'$oid': '66909eb3b72fc3ddba24dd36'}	daily-freelance	False	1994.0	2023-07-09	2015	NCS HealthCare of KY, Inc dba Vangard Labs	n/a	16th Floor	good	NaN	NaN	working	Accounting	NaN	Male	april	True	it's hard for getting job after school life	NaN	674789903	21101.0	NaN	Olorenshaw	lolorenshaw0@yolasite.com	Leslie	teknik-otomasi-industri	NaN	NaN	NaN	NaN	NaN	NaN

	_id	employment-status	first-job	year	birthdate	graduation-year	company-name	industry-sector	Address	quality-of-education	last-name	department	status	position	opinion-of-the-field-of-study	gender	month	salary-meet-the-minimum-wage	improvement-suggestions	first-name	nik	amount-of-salary-and-allownce	other-position	last_name	email	first_name	departement	education-level	institution	Program-of-Study	product-or-service-offered	amount-of-profit	unit-of-profit
3999	{'$oid': '6690b2c1b72fc3ddba24eccc'}	NaN	NaN	2003.0	2024-05-25	2004	NaN	NaN	NaN	not-satisfied	Loosemore	Marketing	entrepreneur	NaN	NaN	Male	july	NaN	saya sangat sulit untuk masuk kuliah	Basilius	3778678078	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Books	{'$numberLong': '55788804323'}	day
4000	{'$oid': '6690b2c1b72fc3ddba24eccd'}	NaN	NaN	2004.0	2023-10-26	1995	NaN	NaN	NaN	poor	Ousley	Services	entrepreneur	NaN	NaN	Female	august	NaN	saya bisa masuk kuliah walaupun harus bersusah payah	Corine	616913931	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Jewelry	{'$numberLong': '21867860224'}	week
4001	{'$oid': '6690b2c1b72fc3ddba24ecce'}	NaN	NaN	1995.0	2024-05-13	1994	NaN	NaN	NaN	excellent	Sleney	Product Management	entrepreneur	NaN	NaN	Agender	september	NaN	saya berhasil masuk ptn impian	Gabrila	5821594561	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Baby	{'$numberLong': '2510993517'}	day
4002	{'$oid': '6690b2c1b72fc3ddba24eccf'}	NaN	NaN	2009.0	2023-11-18	2006	NaN	NaN	NaN	good	Spurman	Human Resources	entrepreneur	NaN	NaN	Female	october	NaN	saya berhasil masuk ptn walaupun bukan impian saya	Aurilia	8847250064	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Shoes	{'$numberLong': '25427321398'}	week
4003	{'$oid': '6690b2c1b72fc3ddba24ecd0'}	NaN	NaN	1987.0	2024-03-14	2008	NaN	NaN	NaN	not-satisfied	Wickie	Engineering	entrepreneur	NaN	NaN	Male	november	NaN	saya sangat sulit untuk masuk kuliah	Dunc	7627887798	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Baby	{'$numberLong': '26741140991'}	month
4004	{'$oid': '6690b2c1b72fc3ddba24ecd1'}	NaN	NaN	1979.0	2024-02-26	1999	NaN	NaN	NaN	poor	Luckwell	Sales	entrepreneur	NaN	NaN	Male	december	NaN	saya bisa masuk kuliah walaupun harus bersusah payah	Jessee	6264888060	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Tools	{'$numberLong': '28146607148'}	month
4005	{'$oid': '6690b2c1b72fc3ddba24ecd2'}	NaN	NaN	2001.0	2023-08-07	2005	NaN	NaN	NaN	excellent	Firby	Business Development	entrepreneur	NaN	NaN	Female	january	NaN	saya berhasil masuk ptn impian	Bonnibelle	3522841859	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Grocery	{'$numberLong': '63713198961'}	month
4006	{'$oid': '6690b2c1b72fc3ddba24ecd3'}	NaN	NaN	2009.0	2023-07-31	2008	NaN	NaN	NaN	good	Swait	Sales	entrepreneur	NaN	NaN	Male	february	NaN	saya berhasil masuk ptn walaupun bukan impian saya	Lucho	9793330066	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Toys	{'$numberLong': '76658580502'}	day
4007	{'$oid': '6690b2c1b72fc3ddba24ecd4'}	NaN	NaN	2003.0	2024-02-27	1993	NaN	NaN	NaN	not-satisfied	Dougan	Product Management	entrepreneur	NaN	NaN	Female	march	NaN	saya sangat sulit untuk masuk kuliah	Ciel	8744184816	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Shoes	{'$numberLong': '44754979229'}	month
4008	{'$oid': '6690b2c1b72fc3ddba24ecd5'}	NaN	NaN	2011.0	2023-12-24	2010	NaN	NaN	NaN	poor	Nesbitt	Support	entrepreneur	NaN	NaN	Female	april	NaN	saya bisa masuk kuliah walaupun harus bersusah payah	Oliy	2715726457	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Tools	{'$numberLong': '66791719424'}	week

Most frequently occurring

	employment-status	year	birthdate	graduation-year	company-name	industry-sector	Address	quality-of-education	last-name	department	status	position	opinion-of-the-field-of-study	gender	month	improvement-suggestions	first-name	nik	amount-of-salary-and-allownce	other-position	last_name	email	first_name	departement	education-level	institution	Program-of-Study	product-or-service-offered	unit-of-profit	# duplicates
1	daily-freelance	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	aegbahwg9yhagw	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	4
0	daily-freelance	1992.0	2024-03-18	1998	Cardinal Health	Finance	Suite 100	poor	NaN	NaN	working	Business Development	NaN	Non-binary	july	hard to get a job for a while	NaN	364263113	99351.0	NaN	Josefer	pjosefer0@typepad.com	Pietrek	bisnis-kontruksi-dan-properti	NaN	NaN	NaN	NaN	NaN	2
2	daily-freelance	2024.0	2001-01-15	2001	JIVALOKA	marketing	Jl . Bumi Karadenan Permai	good	Septanugroho	teknik-otomasi-industri	working	accounting	useful	male	october	improve the cleaning services	Muhammad Aris	3201010439710924	120834021.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	2

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks